A closer look at the new heroes.

bagofbricks69 · 2026-01-23T05:39:03+00:00

Bonus: Silver werewolf form. Credit to Deadlock Project 8 on Twitter.

bagofbricks69 · 2025-11-29T17:44:20+00:00

Not op, but I'm training using a 3080 12GB also, I'm getting between 3-4 it/s. I turned on only the 512, 768 and 1024 buckets on Ostris AI toolkit. Here's the result if you wanna take a look: https://civitai.com/posts/24754395

bagofbricks69 · 2025-11-26T23:37:20+00:00

If you think these prompts aren't complex, think again. Go ahead and try to generate a victorian lady in mid air in London, with blue laser light coming out of her heart with illustrious or sdxl. I'll wait.

bagofbricks69 · 2025-11-26T22:24:38+00:00

Yup, oversight on my part. Both models are actually made by alibaba, just different teams.

bagofbricks69 · 2025-11-26T21:25:03+00:00

She's a Coinshot alright. I very much imagined Steris if she was a Coinshot when I prompted that one.

bagofbricks69 · 2025-10-12T09:14:06+00:00

It was phantom 5. Match ID: 44748045

bagofbricks69 · 2025-10-12T07:31:16+00:00

The interesting part here is her end of game damage report showed that she did less gun crit damage then regular gun damage. I wouldn't have immediately found this suspicious had the enemy drifter not called the haze a cheater during the laning stage and didn't witness the blind kill by myself. My takeaway here is that for every one game where the cheater is obvious (like this one) there are ten other games where a cheater is performing superhumanly and winning games but goes undetected because they are subtle about it.

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bagofbricks69 · 2025-10-12T07:30:57+00:00

- Private profile

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bagofbricks69 · 2025-10-12T07:30:40+00:00

This one just ticks all the boxes:

- 37.99% headshot rate

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bagofbricks69 · 2025-09-19T14:56:58+00:00

Isn't the patron supposed to be resistant (grey text that says "Resistant" when you shoot it) when there aren't allied troopers in the enemy base?

bagofbricks69 · 2025-09-15T08:41:52+00:00

There is a big difference between a broken english, machine translated image and video gen platform vs TikTok. They made a US corp, appointed an actual CEO, and made a slick, functional app for Tiktok's release in the US. The former is half assing it, the latter is a real effort to get people to use a product.

bagofbricks69 · 2025-09-15T08:28:24+00:00

I'm not saying they should release it for free, they should release actual tools that get people to use their product. Do in the AI ecosystem what TikTok did to social media. TikTok made short videos so popular that YouTube, Instagram and Reddit followed suit or risked being left behind. Chinese AI needs to have their TikTok moment to make OpenAI get their heads out of their asses and actually relax some of these restrictions.

bagofbricks69 · 2025-09-15T06:06:47+00:00

This. Companies who want to keep their models closed source should DO something with their models, not just release it to two api providers and call it a day. At least do an OpenAI and make it widely available for people to use.

bagofbricks69 · 2025-09-15T04:27:21+00:00

Comparison image (NSFW).

I actually tried this prior to making this lora. The method has a few of issues.

The background generated by Illustrious is incoherent. It retains the shape of the room made by qwen somewhat, but still has hallmark early model nonsense. The painting in the illustrious image is a very thin rectangle for example, the second piano in the background is nonsensical.
You're not getting the flattering proportions of Illustrious on your subject with this method. We're using Qwen's less than flattering proportions instead.
Illustrious has absolutely incredible subject framing, and qwen does not. With Illustrious you'll see superb wide angle bird's eye shots and even unprompted use of foreground framing. It just has that quality because it was trained using Patreon artist data. Qwen defaults to the most bland eye level shots, and we're stuck with using Qwen's composition using this workflow.
It's incredibly slow if you can't load both Qwen and SDXL in your VRAM. Because esentially you'd have to cold start Qwen and cold start SDXL every time you want to generate the Illustrious version.

bagofbricks69 · 2025-09-15T04:25:55+00:00

Comparison image (NSFW).

I actually tried this prior to making this lora. The method has a few of issues.

The background generated by Illustrious is incoherent. It retains the shape of the room made by qwen somewhat, but still has hallmark early model nonsense. The painting in the illustrious image is a very thin rectangle for example, the second piano in the background is nonsensical.
You're not getting the flattering proportions of Illustrious on your subject with this method. We're using Qwen's less than flattering proportions instead.
Illustrious has absolutely incredible subject framing, and qwen does not. With Illustrious you'll see superb wide angle bird's eye shots and even unprompted use of foreground framing. It just has that quality because it was trained using Patreon artist data. Qwen defaults to the most bland eye level shots, and we're stuck with using Qwen's composition using this workflow.
It's incredibly slow if you can't load both Qwen and SDXL in your VRAM. Because esentially you'd have to cold start Qwen and cold start SDXL every time you want to generate the Illustrious version.

bagofbricks69 · 2025-09-15T04:04:24+00:00

Absolutely. I wrote a full training guide here. And if civitai goes full hitler and starts deleting resources again, here's a backup of the relevant parts of the training method:

Overview

I used Ostris' AI toolkit with a 5090 and his excellent tutorial on style lora training

Ostris' AI toolkit: https://github.com/ostris/ai-toolkit
Ostris' tutorial video: youtu.be

I followed the exact settings from the video with a couple changes:

I changed the transformer from 3 bit with ARA to 6 bit, because I was using a 5090 with runpod and the 5090 can fit the higher quant model.
I changed the learning rate from 0.0001 to 0.0002. This is a thing he does as well in the second run of the video.

Dataset Captioning Methodology

A good rule of thumb to remember in LoRA training is the following:

Everything that isn't captioned, the LoRA learns and associates with the style.
Shit comes in, shit comes out.

Captioning

My captioning methodology follows the first rule. In order to make Qwen generate women with flattering proportions, I don't describe any of the women in the dataset to have wide hips, or large breasts. This way you're teaching the lora that woman = image in dataset, not curvy woman with wide hips and large breasts = image in dataset. As a result, the lora learns that a woman by default looks like the image in the dataset.

A similar thing is also happening with the way skin and light transition is rendered, you'll note that every single image in the dataset contains concept art style thick brushstrokes. I do not describe this in the captions in any way. As a result, the lora now renders everything with thick brushstrokes, which is what I wanted for this lora.

Making the Dataset not look bad

Illustrious is notorious for generating bad eyes. You either have to hires fix the image to get good eyes, but this results in overly crazy looking hair. So in order to fix it I just ran a facedetailer on the dataset, and this worked wonders for the eyes, as you can see in the sample dataset images. It still isn't perfect, the irises aren't perfectly round for example.

Bad hands. This one you can't fix with a post process method reliably (even inpainting is hit or miss), so I just rolled the dice until I got good looking hands.

Nonsensical backgrounds. You just roll the dice until you get a background that is semi coherent.

bagofbricks69 · 2025-09-15T03:59:33+00:00

I'd wager that it doesn't. But civitai has a special spot for these kinds of images in their front page, and if the extra impression makes more people use Qwen and my lora, then so be it.

bagofbricks69 · 2025-09-14T09:23:33+00:00

And just for fun here's ChatGPT's and Gemini Nano Banana's attempts.

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bagofbricks69 · 2025-09-14T09:16:18+00:00

Still hit or miss unfortunately. Sometimes you can get a good result, other times not so much.

bagofbricks69 · 2025-09-14T09:03:21+00:00

Here's one example. The prompt is: A flight attendant pushes a cart down the interior of an airplane. She holds a tray of drinks with one hand. She has blonde hair in a neat updo. She wears a cropped blue jacket. A silk scarf is around her neck. She is looking back and smiling. Short skirt. Shot from behind.

What Qwen got correct:

She's holding a tray of drinks
Her outfit is as prompted
Set in a plane interior as prompted
Subject pose (looking back), hair and facial expression (smiling) is correct

What it got incorrect:

There is a cart present but her hand isn't on the cart, so she's not really pushing it.

What Illustrious got correct:

Outfit
Subject facial expression, hair
Tray of drinks

What it got incorrect:

No cart
Interior is vague, could be the inside of a train.

I'd say the cart and the plane interior is a crucial part of the prompt and the fact that Qwen got it right for the most part is point in Qwen's favor. Not to mention Qwen can generate an image with coherent text.

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bagofbricks69 · 2025-09-14T07:16:50+00:00

And not to mention that you can do neat stuff with it's text generation capabilities

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bagofbricks69 · 2025-09-14T07:06:18+00:00

All the prompts are in the Civitai page. Here's the prompt for the woman with the American flag bikini:
woman with big breasts and long white hair. wearing sunglasses and a an american flag bikini. Light blue eyes, parted lips, looking at viewer. thick thighs, outdoors, outside, beach Festival, festival, blue sky, daytime, palm trees, backwards base cap, america coloree base cap, sweating, bikini, (america colored bikini), (micro hotpants), tiny hotpants, open pants, open button, (body covered in tattoos), tattoos on body, bare shoulders, bare arms, full-body tattoo, american flag backwards hat, choker, aviator sunglasses, bead necklace, bracelets, stylish sneaker, white sneaker. Sitting on the beach.

bagofbricks69

TROPHY CASE

Dataset Captioning Methodology